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GitHub / ahmedgh970 / Autoencoders_Adversarial_Training_UAD
Adversarially Training of Autoencoders for Unsupervised Anomaly Segmentation
Stars: 5
Forks: 0
Open Issues: 0
License: gpl-3.0
Language: Jupyter Notebook
Repo Size: 60.5 KB
Dependencies:
18
Created: over 2 years ago
Updated: almost 2 years ago
Last pushed: almost 2 years ago
Last synced: 2 months ago
Topics: anomaly-segmentation, autoencoders, convolutional-autoencoder, deep-neural-networks, flair, mri-brain-segmentation, pgd-adversarial-attacks, reconstruction, resnet-50, unsupervised-learning, variational-autoencoder
Files
Dependencies
- DateTime *
- SimpleITK *
- bunch *
- einops *
- imageio *
- matplotlib *
- medpy *
- nibabel *
- numpy *
- opencv-python *
- plot_keras_history *
- pynrrd *
- scikit-image *
- scikit-learn *
- scipy *
- seaborn *
- sklearn *
- tensorflow-addons *